In R, the toupper() function is used to convert a string to uppercase. For example, toupper("Hello") would return "HELLO".

Base R plotting offers more flexibility, allowing for a wider range of customization and plot types. However, ggplot2 provides a more structured and consistent grammar of graphics, making it easier to create complex plots. The choice between the two often depends on personal preference and the specific requirements of the plot.

To determine the data type of a variable in R, you would use the typeof() function on the variable. The typeof() function returns a character string representing the data type of the object.

You can use conditional statements like if-else in combination with the print() function to display different messages based on the value of a variable. This allows you to make the output more user-friendly and informative.

R handles missing values in statistical calculations by providing functions that allow for exclusion of missing values from calculations. For example, many statistical functions in R have an na.rm parameter that, when set to TRUE, ignores missing values and performs calculations on the available data. This allows for accurate statistical analyses even when data contain missing values.

To write a recursive function in R that calculates the factorial of a number, you can use the following code: factorial <- function(n) { if (n <= 1) { return(1) } else { return(n * factorial(n - 1)) } }. The function checks if the input n is less than or equal to 1. If it is, it returns 1 (base case). Otherwise, it multiplies n with the factorial of n - 1 (recursive case). This recursive calculation continues until the base case is reached.

Including double quotes within a string in R is commonly required when writing a string that represents a quote or dialogue. For example, "She said, "Hello!"" represents the string She said, "Hello!".

Vectorization in R allows you to apply functions or operations directly to vectors or data frames, which eliminates the need for explicit if-else statements. The ifelse() function is specifically designed for vectorized conditional operations, providing a concise and efficient alternative to if-else statements when working with vectors or data frames.

To calculate the median of each column in a data frame in R, you would use the apply() function. By specifying the appropriate margin argument (2 for columns), you can apply the median() function across each column of the data frame.

One way to handle this is by using the is.finite() function which checks whether the value is finite or not. This function returns FALSE if the value is Inf or NaN and TRUE otherwise. Depending on the use case, you can then decide how to handle these non-finite values.

To customize the appearance of an R scatter plot, including changing colors, markers, and sizes, you can use the col parameter to change colors, the pch parameter to change markers, and the cex parameter to change the size of the points. These graphical parameters can be specified within the plot() function.

When performing 'AND' and 'OR' operations in R, if either operand is 'NA', the result will be 'NA' for both 'AND' and 'OR' operations. This is because the presence of 'NA' indicates that the value is missing or unknown, resulting in an unknown outcome for the logical operation.